Add artifacts

app.py

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+# !pip install gradio ipywidgets
+import pandas as pd
+import gradio as gr
+import joblib
+
+# "Artifacts"
+pipeline = joblib.load("pipeline.joblib")
+label_pipeline = joblib.load("label_pipeline.joblib")
+cities = joblib.load("cities.joblib")
+
+def predict(city, location, area, bedrooms, baths):
+    sample = dict()
+    sample["city"] = city
+    sample["location"] = location
+    sample["Area_in_Marla"] = area # Column names matching feature names
+    sample["bedrooms"] = bedrooms
+    sample["baths"] = baths
+
+    price = pipeline.predict(pd.DataFrame([sample]))
+    price = label_pipeline.inverse_transform([price])
+    
+    return int(price[0][0])
+
+# https://www.gradio.app/guides
+with gr.Blocks() as blocks:
+    city = gr.Dropdown(cities, value=cities[0], label="City")
+    location = gr.Textbox(label="Location")
+    area = gr.Number(label="Area", value=1, minimum=0.5, step=0.5)
+    bedrooms = gr.Slider(label="Bedrooms", minimum=0, maximum=10, step=1)
+    baths = gr.Slider(label="Baths", minimum=0, maximum=10, step=1)
+
+    price = gr.Number(label="Price")
+
+    inputs = [city, location, area, bedrooms, baths]
+    outputs = [price]
+
+    predict_btn = gr.Button("Predict")
+    predict_btn.click(predict, inputs=inputs, outputs=outputs)
+
+if __name__ == "__main__":
+    blocks.launch() # Local machine only
+    # blocks.launch(server_name="0.0.0.0") # LAN access to local machine
+    # blocks.launch(share=True) # Public access to local machine

requirements.txt

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+aiofiles==23.2.1
+altair==5.2.0
+annotated-types==0.6.0
+anyio==4.2.0
+appnope==0.1.3
+asttokens==2.4.1
+attrs==23.2.0
+certifi==2023.11.17
+charset-normalizer==3.3.2
+click==8.1.7
+colorama==0.4.6
+comm==0.2.1
+contourpy==1.2.0
+cycler==0.12.1
+debugpy==1.8.0
+decorator==5.1.1
+executing==2.0.1
+fastapi==0.109.0
+ffmpy==0.3.1
+filelock==3.13.1
+fonttools==4.47.2
+fsspec==2023.12.2
+gradio==4.16.0
+gradio_client==0.8.1
+h11==0.14.0
+httpcore==1.0.2
+httpx==0.26.0
+huggingface-hub==0.20.3
+idna==3.6
+importlib-resources==6.1.1
+ipykernel==6.29.0
+ipython==8.20.0
+jedi==0.19.1
+Jinja2==3.1.3
+joblib==1.3.2
+jsonschema==4.21.1
+jsonschema-specifications==2023.12.1
+jupyter_client==8.6.0
+jupyter_core==5.7.1
+kiwisolver==1.4.5
+markdown-it-py==3.0.0
+MarkupSafe==2.1.4
+matplotlib==3.8.2
+matplotlib-inline==0.1.6
+mdurl==0.1.2
+nest-asyncio==1.6.0
+numpy==1.26.3
+orjson==3.9.12
+packaging==23.2
+pandas==2.2.0
+parso==0.8.3
+pexpect==4.9.0
+pillow==10.2.0
+platformdirs==4.1.0
+prompt-toolkit==3.0.43
+psutil==5.9.8
+ptyprocess==0.7.0
+pure-eval==0.2.2
+pydantic==2.6.0
+pydantic_core==2.16.1
+pydub==0.25.1
+Pygments==2.17.2
+pyparsing==3.1.1
+python-dateutil==2.8.2
+python-multipart==0.0.6
+pytz==2023.4
+PyYAML==6.0.1
+pyzmq==25.1.2
+referencing==0.33.0
+requests==2.31.0
+rich==13.7.0
+rpds-py==0.17.1
+ruff==0.1.15
+scikit-learn==1.4.0
+scipy==1.12.0
+semantic-version==2.10.0
+shellingham==1.5.4
+six==1.16.0
+sniffio==1.3.0
+stack-data==0.6.3
+starlette==0.35.1
+threadpoolctl==3.2.0
+tomlkit==0.12.0
+toolz==0.12.1
+tornado==6.4
+tqdm==4.66.1
+traitlets==5.14.1
+typer==0.9.0
+typing_extensions==4.9.0
+tzdata==2023.4
+urllib3==2.1.0
+uvicorn==0.27.0.post1
+wcwidth==0.2.13
+websockets==11.0.3